Observer and automated estimation data from drone-based imagery of blackbird flocks foraging in commercial sunflower

We used drones to capture images of mixed-species blackbird (Icteridae) flocks damaging sunflower (Helianthus annuus) in North Dakota. Images consisted of an airborne flock with a sky background, creating a strong color contrast for automated bird detection and counting. We analyzed imagery from 60 flights using ImageJ and obtained automated counts. We also asked 20 biologists, ranging from 0-25 years of self-reported experience, to provide estimates for all 60 images in a single sitting. They were asked to make quick estimates (5-10 seconds per photo), to count birds within the sky background, and to zoom in on photos when needed. Photos were randomly ordered and all biologists were given photos in the same order. This study was implemented between September 2021 through October 2022 in multiple counties in North Dakota, USA where blackbird damage to sunflowers is prevalent. This data publication contains the data and R code used to analyze these data as well as the 60 drone images.
We designed the study to evaluate the role of flock size, biologist experience, and photo order on the ability of a biologist to make estimates close to the automated count.
For more information about this study and these data, see Duttenhefner and Klug (2025).

These data were published on 01/22/2025. On 03/12/2025, the metadata was updated to include reference to newly published article.